Senior Machine Learning Engineer

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Design and develop the machine learning engineering for the pricing engine.

• Create inference serving, training pipelines, and feature engineering for real-time, low-latency models using Ray.

• Construct chained model pipelines on Ray Serve, focusing on composition, low latency, and strategies for updates.

• Develop distributed training pipelines with Ray Train/Data, hyperparameter optimization through Ray Tune, and tenant-specific trained models featuring resilient checkpointing.

• Specify and implement features in the Feast/Redis feature store, ensuring alignment between training and production environments.

• Optimize and implement linear programming and offline reinforcement learning components within the pricing pipeline.

• Monitor model drift, validate versions, and provide explainability using SHAP in collaboration with MLOps.

• Act as a technical authority, mentor team members, and establish effective, scalable solutions.

• Oversee transitions with data scientists, receive data from data engineers, and facilitate delivery to the MLOps/Platform team for deployment and operational needs.

⛳️ Requirements

• Demonstrated experience in deploying machine learning models into production.

• Proficient in Python and possess solid software engineering principles (APIs, testing, clean code).

• Experience with serving and inference optimization for achieving low latency.

• Knowledge of containerization (Docker) and familiarity with MLOps workflows (registry, deployment).

• Comfortable utilizing AI-assisted development tools (Claude Code).

• Proficient with Ray (Serve, Train, Tune, Data, RLlib).

• Familiarity with MLflow, Feast, and Redis.

• Experience in linear programming (Gurobi, HiGHS).

• Knowledge of offline reinforcement learning.

• Experience with Iceberg data reading.

• Nice to have: familiarity with vLLM, LiteLLM, and multi-tenant architectures.

🏝️ Benefits

• Continuous professional development opportunities.

• Flexible remote work options.

• Six-month project duration, with potential for extension or transition to permanent employment.